3 citations · 3 across the 3 of their papers we have counts for
3 papers
cs.SE2024
Exploring the Capabilities of LLMs for Code Change Related Tasks
Lishui Fan, Jiakun Liu, Zhongxin Liu +3
Developers deal with code-change-related tasks daily, e.g., reviewing code. Pre-trained code and code-change-oriented models have been adapted to help developers with such tasks. R…
cs.SE2024
APIDocBooster: An Extract-Then-Abstract Framework Leveraging Large Language Models for Augmenting API Documentation
Chengran Yang, Jiakun Liu, Bowen Xu +5
API documentation is often the most trusted resource for programming. Many approaches have been proposed to augment API documentation by summarizing complementary information from…
cs.SE2023★ 3 cited
The Devil is in the Tails: How Long-Tailed Code Distributions Impact Large Language Models
Xin Zhou, Kisub Kim, Bowen Xu +3
Learning-based techniques, especially advanced Large Language Models (LLMs) for code, have gained considerable popularity in various software engineering (SE) tasks. However, most…